Propaganda Analysis Project

Call for Papers (Draft)

The advent of Internet as a mass media has had a profound effect on the way political agendas and ideological messages are spread to larger and larger audiences.

Nowadays, social media and messaging apps, may be exploited not only by large institutions and governments, but also by small organisations or individuals to reach an audience of unprecedented size. Such strategies have been reported to have been used to influence voters' opinions in the U.S. 2016 elections and the referendum on Brexit. Such alleged consequences have inevitably attracted the attention of the large institutions, government and social media companies and induced them to search for counter measures.

The topic is of great interest to the research community, there have been a special issue of Big Data on computational propaganda, there is an ongoing shared task on Hyperpartisanship and extreme bias, a workshop on fact extraction and verification, and an upcoming hackaton on propaganda identification. The problem of detecting the use and the spreading of propaganda and extreme bias in society has been tackled in other fields such as network analysis, social sciences/data analysis and psychology. On the NLP side, efforts have focused on identifying if a full news article is real, fake, propaganda, or satire, if it is propaganda or not and on the detection of hyperpartisanship.

In this workshop we aim at bringing together the research efforts in natural language processing and expose them to ideas from those different communities.

[full call will be available upon proposal acceptance]